In [1]:

from pathlib import Path
import utils
import trackmate_utils
import holoviews as hv
import panel as pn
pn.extension('tabulator')
hv.extension('bokeh')
import numpy as np

from pathlib import Path import utils import trackmate_utils import holoviews as hv import panel as pn pn.extension('tabulator') hv.extension('bokeh') import numpy as np

1. Exploring Metric & Merged Tracks¶

Define data paths for data and configs. Using the utils.run_analysis() method we get a segmentation map and TrackMate results.

In [2]:

from pathlib import Path

import pandas as pd

import utils
import trackmate_utils


base_data_path = Path(r"data/fucci_60_frames")
red_stack_path = base_data_path / "red.tif"
green_stack_path = base_data_path / "green.tif"

base_model_path = Path(r"models")
red_segmentation_model = base_model_path / "cellpose/nuclei_red_v2"
green_segmentation_model = base_model_path / "cellpose/nuclei_green_v2"

red_segmentation_map = utils.read_stack(base_data_path / "red_segmented.tiff")
green_segmentation_map = utils.read_stack(base_data_path / "green_segmented.tiff")

tm_red = trackmate_utils.TrackmateXML(base_data_path / "red_segmented.tiff.xml")
tm_green = trackmate_utils.TrackmateXML(base_data_path / "green_segmented.tiff.xml")

red_stack = utils.read_stack(base_data_path / "red.tif")
green_stack = utils.read_stack(base_data_path / "green.tif")

# metric = trackmate_utils.CartesianSimilarity(tm_red, tm_green)
# metric_df = metric.calculate_metric_for_all_tracks()
# metric_df.to_hdf(base_data_path / "metric.h5", key="metric")
metric_df = pd.read_hdf(base_data_path / "metric.h5", key="metric")
metric = trackmate_utils.CartesianSimilarityFromFile(tm_red, tm_green, metric_df)

from pathlib import Path import pandas as pd import utils import trackmate_utils base_data_path = Path(r"data/fucci_60_frames") red_stack_path = base_data_path / "red.tif" green_stack_path = base_data_path / "green.tif" base_model_path = Path(r"models") red_segmentation_model = base_model_path / "cellpose/nuclei_red_v2" green_segmentation_model = base_model_path / "cellpose/nuclei_green_v2" red_segmentation_map = utils.read_stack(base_data_path / "red_segmented.tiff") green_segmentation_map = utils.read_stack(base_data_path / "green_segmented.tiff") tm_red = trackmate_utils.TrackmateXML(base_data_path / "red_segmented.tiff.xml") tm_green = trackmate_utils.TrackmateXML(base_data_path / "green_segmented.tiff.xml") red_stack = utils.read_stack(base_data_path / "red.tif") green_stack = utils.read_stack(base_data_path / "green.tif") # metric = trackmate_utils.CartesianSimilarity(tm_red, tm_green) # metric_df = metric.calculate_metric_for_all_tracks() # metric_df.to_hdf(base_data_path / "metric.h5", key="metric") metric_df = pd.read_hdf(base_data_path / "metric.h5", key="metric") metric = trackmate_utils.CartesianSimilarityFromFile(tm_red, tm_green, metric_df)

In [33]:

print(f'we have {len(tm_red.tracks.TrackID.unique())} red, {len(tm_green.tracks.TrackID.unique())} green tracks')

print(f'we have {len(tm_red.tracks.TrackID.unique())} red, {len(tm_green.tracks.TrackID.unique())} green tracks')

we have 145 red, 72 green tracks

2. Measure Flouresence Over Time¶

Add plot

In [4]:

%load_ext autoreload
%autoreload 2

%load_ext autoreload %autoreload 2

In [5]:

metric_df.query('2 < metric < 10')

metric_df.query('2 < metric < 10')

Out[5]:

	red_track	green_track	metric
29	30	21	2.004808
30	3	52	2.027253
31	22	59	2.470495
32	15	66	2.984784
33	55	63	3.131836
34	43	19	6.059927

In [6]:

valid_tracks = metric_df.query('metric < 2.1')
valid_tracks.describe()

valid_tracks = metric_df.query('metric < 2.1') valid_tracks.describe()

Out[6]:

	red_track	green_track	metric
count	31.000000	31.000000	31.000000
mean	36.580645	31.967742	1.513820
std	21.734418	19.147644	0.295953
min	0.000000	0.000000	1.018302
25%	24.500000	17.000000	1.208442
50%	34.000000	35.000000	1.515348
75%	53.500000	47.500000	1.754014
max	71.000000	62.000000	2.027253

In [7]:

excluded_tracks = pd.concat([valid_tracks.query('red_track == @r and green_track == @g') for r,g in ((53,62),(6,14),(71, 31),(24, 27),(19, 9))]).index
valid_tracks = valid_tracks.drop(excluded_tracks)
valid_tracks.describe()

excluded_tracks = pd.concat([valid_tracks.query('red_track == @r and green_track == @g') for r,g in ((53,62),(6,14),(71, 31),(24, 27),(19, 9))]).index valid_tracks = valid_tracks.drop(excluded_tracks) valid_tracks.describe()

Out[7]:

	red_track	green_track	metric
count	26.000000	26.000000	26.000000
mean	36.961538	32.615385	1.523143
std	21.270601	19.193909	0.297460
min	0.000000	0.000000	1.018302
25%	28.250000	20.250000	1.227805
50%	34.500000	38.000000	1.515829
75%	53.250000	47.750000	1.750306
max	70.000000	58.000000	2.027253

In [8]:

track = valid_tracks.iloc[0]
track

track = valid_tracks.iloc[0] track

Out[8]:

red_track      32.000000
green_track    40.000000
metric          1.018302
Name: 0, dtype: float64

In [9]:

merged_track = metric.merge_tracks(32,40)
merged_track

merged_track = metric.merge_tracks(32,40) merged_track

Out[9]:

	ID	frame	POSITION_X	POSITION_Y	PERIMETER	image_id	AREA	ROI	roi_polygon	ELLIPSE_MAJOR	ELLIPSE_MINOR	color	source_track
0	736	0	65.728445	202.089107	116.11824370003114	26	866.0	[(1.7715550423402533, 14.41089299461126), (3.7...	POLYGON ((68 217, 70 216, 72 216, 73 215, 75 2...	20.291765089571808	13.70531505224533	red	red
1	760	1	71.391949	196.740581	115.39641876807232	23	871.5	[(14.108051252629565, 14.759418626888504), (14...	POLYGON ((86 212, 86 210, 88 209, 90 206, 91 2...	21.374369189708005	13.399444522800408	red	red
2	494	2	71.042601	189.803625	120.58961482031928	23	892.0	[(11.45739910313901, 16.69637518684604), (12.4...	POLYGON ((83 207, 84 205, 86 205, 86 203, 88 2...	20.40135288822979	13.965682099487488	red	red
3	391	3	74.068707	186.231001	116.3744297518984	21	857.5	[(11.43129251700681, 16.26899902818269), (12.4...	POLYGON ((86 203, 87 201, 89 201, 90 199, 91 1...	20.399578962898765	14.070220428457475	red	red
4	444	4	82.523703	180.657591	114.95010692219705	27	780.5	[(11.97629724535554, 15.842408712363863), (15....	POLYGON ((95 197, 99 190, 100 188, 100 184, 10...	20.334182996872435	12.662916516494565	red	red
5	339	5	91.56938	176.723927	107.8440407924095	26	749.5	[(8.930620413609077, 15.776072937513874), (11....	POLYGON ((101 193, 104 191, 106 190, 107 188, ...	19.75199745076159	12.34746985943662	red	red
6	1599	6	99.556633	171.751282	108.24163657932809	27	747.5	[(6.943366778149397, 15.748717948717967), (8.9...	POLYGON ((107 188, 109 187, 111 187, 112 186, ...	19.572237562684293	12.616880908415732	red	red
7	771	7	111.74149	168.659517	111.0764782026885	29	827.5	[(9.758509566968783, 16.840483383685807), (13....	POLYGON ((122 186, 126 182, 128 181, 130 177, ...	21.12904241487818	12.862358732803552	red	red
8	2107	8	118.414195	170.740411	109.3563041130157	29	843.0	[(3.085804665875841, 17.75958877026494), (5.08...	POLYGON ((122 189, 124 188, 126 188, 129 186, ...	19.280903420341502	14.34783113238613	red	red
9	742	9	123.609063	172.62404	111.3521091648572	27	868.0	[(6.890937019969272, 18.875960061443948), (11....	POLYGON ((131 192, 136 186, 138 185, 138 183, ...	20.297499900252678	14.002487234289353	red	red
10	932	10	128.309751	174.805423	117.85407190410241	28	943.5	[(5.1902490726020005, 21.69457692987106), (8.1...	POLYGON ((134 197, 137 194, 139 194, 140 192, ...	21.883407857379485	13.993156941709945	red	red
11	926	11	132.018802	171.702995	119.41223997479155	22	979.5	[(8.481197890079955, 19.797005274800057), (11....	POLYGON ((141 192, 144 190, 146 189, 147 185, ...	22.238618483986546	14.331585951373167	red	red
12	1088	12	138.011852	169.775298	123.72726948395658	24	1019.5	[(7.488147784861837, 20.7247016511362), (10.48...	POLYGON ((146 191, 149 189, 151 188, 155 183, ...	22.60726816764416	14.524438723918653	red	red
13	1231	13	142.618794	160.895712	122.58311404261416	22	1034.0	[(7.881205673758842, 20.604287556415215), (8.8...	POLYGON ((151 182, 152 180, 154 180, 158 176, ...	22.183475397887342	15.139483794105766	red	red
14	997	14	150.315073	148.52005	116.72921462019963	21	931.0	[(5.184926602219832, 19.979949874686724), (7.1...	POLYGON ((156 169, 158 168, 159 167, 162 164, ...	20.49377315803756	14.704651861993371	red	red
15	126	15	154.636106	146.383226	111.20916221628806	20	853.5	[(5.8638937707479215, 19.116774067564933), (7....	POLYGON ((161 166, 163 163, 164 161, 170 156, ...	19.415746732400837	14.61030428827945	red	red
16	1255	16	162.668709	147.5103	117.57152710834744	23	938.5	[(8.831291067305983, 17.98969987568816), (10.8...	POLYGON ((172 166, 174 165, 175 164, 178 161, ...	21.00608140822603	14.636174866599342	red	red
17	1256	17	168.9485	150.571808	120.6614177273773	25	972.5	[(8.551499571551005, 18.928191945158517), (11....	POLYGON ((178 170, 181 167, 182 166, 184 166, ...	21.168613687183537	15.042433876580322	red	red
18	921	18	174.48235	154.967305	120.29186150469945	22	991.5	[(6.017650025214323, 18.532694570516043), (8.0...	POLYGON ((181 174, 183 173, 185 173, 188 171, ...	21.530132238319275	14.743861682565539	red	red
19	62	19	178.590729	155.676407	116.45701582740757	26	924.0	[(9.909271284271284, 16.82359307359306), (13.9...	POLYGON ((189 173, 193 169, 195 168, 197 164, ...	20.892016825017176	14.52020993492408	red	red
20	1113	20	182.900713	156.213012	118.24709943782678	29	935.0	[(9.599286987522305, 17.286987522281663), (12....	POLYGON ((193 174, 196 171, 198 171, 199 169, ...	20.43092323866347	14.789647338887233	red	red
21	155	21	185.487459	156.238095	119.41348240555209	28	917.0	[(9.01254089422028, 18.26190476190476), (10.01...	POLYGON ((195 175, 196 173, 198 173, 199 171, ...	20.582639699001785	14.42099676813598	red	red
22	153	22	192.547256	158.620088	118.48769254872398	29	984.0	[(11.95274390243901, 17.879911924119256), (14....	POLYGON ((205 177, 208 172, 210 171, 211 159, ...	21.284755391810073	15.195173339653872	red	red
23	1195	23	197.982806	154.678331	118.8756897169512	26	964.5	[(11.517193710039749, 17.821669258683244), (12...	POLYGON ((210 173, 211 171, 213 171, 214 169, ...	21.43305300355499	14.710901953372462	red	red
24	1634	24	204.461785	155.853535	120.16909925048742	27	990.0	[(8.038215488215485, 20.646464646464636), (14....	POLYGON ((213 177, 219 172, 221 171, 221 165, ...	22.072990112755598	14.570070673424956	red	red
25	1636	25	206.212968	152.10557	118.6064053696176	26	957.5	[(4.2870322019147125, 19.39442993907744), (6.2...	POLYGON ((211 172, 213 171, 215 171, 218 169, ...	20.542740181176683	14.964421416750909	red	red
26	1807	26	207.437396	137.793207	117.92703272504544	24	1001.0	[(11.062604062604066, 17.706793206793208), (17...	POLYGON ((219 156, 225 151, 226 149, 226 141, ...	21.24463148132436	15.371200487363355	red	red
27	1942	27	211.625281	128.103946	122.55025591783964	21	1039.0	[(10.874719281360285, 17.396053897978817), (13...	POLYGON ((223 146, 226 143, 228 143, 229 141, ...	21.601933255197757	15.689790281500299	red	red
28	2048	28	217.412929	115.897897	120.13888808576206	20	1014.5	[(8.087070806637115, 16.602102842122548), (10....	POLYGON ((226 133, 228 132, 229 131, 231 131, ...	20.86133357675962	15.555337354387452	red	red
29	1341	29	213.428847	101.455485	116.33514833812384	18	951.0	[(7.071153172099542, 15.044514546091833), (9.0...	POLYGON ((221 117, 223 116, 225 116, 227 116, ...	20.98690323787094	14.670076341560621	red	red
30	2328	30	211.173929	88.751024	112.82286368397108	16	895.0	[(1.326070763500951, 15.748975791433892), (3.3...	POLYGON ((213 105, 215 104, 216 103, 226 101, ...	20.013190419211078	14.688402789364249	red	red
31	26	31	211.111431	82.658611	113.29503427027856	16	869.0	[(8.388569236670492, 14.84138856923667), (11.3...	POLYGON ((220 98, 223 96, 225 95, 227 91, 229 ...	19.285968730936283	14.544419262507274	red	red
32	564	32	213.140527	80.534086	106.52388923243727	16	797.0	[(2.3594730238393993, 14.965913843580097), (4....	POLYGON ((216 96, 218 95, 219 93, 226 90, 228 ...	18.85278914637469	14.095173259973349	red	red
33	460	33	216.308993	77.98453	108.33332741146353	16	808.0	[(1.1910066006600744, 14.515470297029708), (10...	POLYGON ((218 93, 227 89, 229 88, 234 82, 235 ...	19.064033544644598	13.686073950799944	red	red
34	1774	34	217.770898	79.522592	107.52326888036792	18	811.5	[(-0.27089751489012315, 15.977408092010677), (...	POLYGON ((218 96, 228 90, 230 89, 235 83, 236 ...	18.804825492688472	14.299392501195987	red	red
39	2156	35	218.378501	83.182325	106.83468312837819	19	791.5	[(2.1214992630027325, 15.031375026321328), (5....	POLYGON ((221 98, 224 96, 226 96, 229 93, 231 ...	18.844243298328518	13.81513080304294	yellow	red
40	1899	36	218.680683	86.017933	107.01288875487856	22	761.0	[(4.819316688567682, 14.89575120455541), (6.81...	POLYGON ((224 101, 226 100, 226 98, 228 98, 22...	17.53115188500524	14.248301019329121	yellow	red
41	2228	37	218.197835	91.137032	103.30508929922131	23	770.0	[(6.302164502164487, 14.725108225108215), (9.3...	POLYGON ((225 106, 228 104, 230 103, 233 98, 2...	16.71794828268125	15.10075936015021	yellow	red
42	2405	38	218.186362	91.795643	105.91250223741798	23	787.0	[(5.313638288860659, 15.015883100381188), (7.3...	POLYGON ((224 107, 226 106, 228 106, 229 104, ...	16.94191734680013	15.284064995179081	yellow	red
43	2615	39	217.521277	91.30479	103.41687417265716	21	775.5	[(3.9787234042553052, 14.385772619815185), (5....	POLYGON ((222 106, 224 105, 226 105, 229 103, ...	17.52449159199243	14.599792751538097	yellow	red
44	3084	40	219.023748	91.158047	107.67892090902448	20	779.0	[(-0.5237483953787034, 13.555626872058184), (4...	POLYGON ((219 105, 224 103, 226 103, 230 101, ...	19.07557387593079	13.52330730878993	yellow	red
45	3463	41	224.028936	89.69076	107.94767771994808	21	803.5	[(-5.528935905413817, 14.017216345156598), (-3...	POLYGON ((219 104, 221 103, 223 103, 225 103, ...	20.52708946899041	12.799747346282482	yellow	red
46	3261	42	233.199168	86.063961	115.62083409522423	19	841.0	[(-2.6991676575505323, 14.684304399524379), (-...	POLYGON ((231 101, 233 100, 235 100, 243 95, 2...	22.542124824356815	12.267042258889465	yellow	red
47	3287	43	237.634815	83.899027	114.86839366538844	18	787.5	[(-6.134814814814803, 14.812275132275133), (-4...	POLYGON ((232 99, 234 98, 235 97, 237 97, 239 ...	22.698134341929453	11.249174871071286	yellow	red
48	2475	44	242.556855	83.655277	111.96090316542035	17	727.0	[(-6.0568546538285375, 15.336084364970205), (-...	POLYGON ((237 99, 240 97, 242 96, 244 96, 248 ...	22.13965946812896	10.865698002244075	yellow	red
49	2544	45	245.485528	81.128107	108.83049521739171	18	702.5	[(-3.985527876631096, 14.653855278766315), (6....	POLYGON ((242 96, 252 90, 254 89, 254 87, 257 ...	22.828693886050488	10.257889523665987	yellow	red
50	3057	46	246.560833	80.876782	111.52935425969349	19	668.5	[(-7.06083271004735, 15.060334081276494), (-5....	POLYGON ((240 96, 242 95, 243 93, 245 93, 246 ...	22.099318550429302	9.849607900611668	yellow	red
51	2686	47	247.410141	78.870321	106.58318341313534	17	664.0	[(-2.910140562249012, 11.962349397590359), (2....	POLYGON ((245 91, 250 88, 252 87, 256 86, 258 ...	22.288453200065845	9.779043137139972	yellow	red
52	903	48	251.905195	84.599728	110.58229965913571	13	770.0	[(3.59480519480519, 12.78311688311689), (10.59...	POLYGON ((256 98, 263 94, 265 93, 265 91, 267 ...	21.42531062433394	11.815366666788258	yellow	green
53	985	49	248.816795	90.524167	120.3272226708876	14	977.5	[(6.683205456095493, 14.631884057971021), (7.6...	POLYGON ((256 106, 257 104, 262 101, 264 100, ...	23.10645662458693	13.889286573264329	yellow	green
54	1058	50	243.853229	92.434794	126.19690621118964	13	1089.0	[(1.646770737679816, 17.5754514845424), (3.646...	POLYGON ((246 111, 248 110, 250 110, 255 107, ...	22.53293727713466	16.291730272105433	yellow	green
55	1021	51	242.183908	93.715079	129.91287125032758	14	1160.0	[(3.316091954022994, 17.436350574712648), (5.3...	POLYGON ((246 112, 248 111, 250 111, 253 109, ...	22.734219225270902	16.628738788116344	yellow	green
56	1097	52	240.704864	97.399249	128.80137306505006	15	1165.0	[(4.7951359084406135, 17.685693848354788), (6....	POLYGON ((246 116, 248 115, 249 114, 252 111, ...	22.357377886606056	16.718468184377684	yellow	green
57	1202	53	240.922222	95.655919	130.5049334495447	15	1200.0	[(1.5777777777777544, 18.41083333333333), (10....	POLYGON ((243 115, 252 111, 254 110, 260 100, ...	23.395698169359886	16.91659746786962	yellow	green
58	1280	54	243.494198	90.377168	130.1159309136902	15	1206.5	[(1.0058019063406505, 17.851636966431826), (4....	POLYGON ((245 109, 248 107, 250 106, 252 106, ...	23.76582596982824	16.449634542371665	yellow	green
59	1289	55	246.158782	85.040545	131.6973474161899	14	1226.0	[(-0.6587819467101781, 18.4184339314845), (10....	POLYGON ((246 104, 257 100, 259 99, 261 96, 26...	22.985828831614352	17.138055214068775	yellow	green
35	1236	56	248.417777	82.971134	131.88291495639214	14	1238.5	[(6.082223119364812, 17.52886556318127), (9.08...	POLYGON ((255 101, 258 99, 260 98, 261 96, 263...	23.25770672129052	17.401466053846903	green	green
36	1135	57	247.543466	81.087209	129.60892096092562	15	1204.0	[(5.956533776301228, 17.412790697674424), (15....	POLYGON ((254 99, 264 93, 266 92, 269 87, 270 ...	22.796772308990608	17.26152532871113	green	green
37	1193	58	248.17074	81.75852	131.00663191374827	15	1227.5	[(6.329260013577738, 17.741479972844544), (11....	POLYGON ((255 100, 260 97, 262 96, 264 96, 266...	22.999463921251163	17.412546098156817	green	green
38	1313	59	249.813302	83.264847	127.59110780359201	15	1181.5	[(10.68669770066299, 17.235153054027364), (13....	POLYGON ((261 101, 264 99, 266 98, 270 93, 271...	23.063837581979733	16.626352282097233	green	green

In [10]:

df = trackmate_utils.measure_merged(merged_track, green_segmentation_map, green_stack, red_segmentation_map, red_stack)
df

df = trackmate_utils.measure_merged(merged_track, green_segmentation_map, green_stack, red_segmentation_map, red_stack) df

Out[10]:

	ID	frame	POSITION_X	POSITION_Y	PERIMETER	image_id	AREA	ROI	roi_polygon	ELLIPSE_MAJOR	...	color	source_track	mean_red	std_red	mean_green	std_green	low_red	high_red	low_green	high_green
0	736	0	65.728445	202.089107	116.11824370003114	26	866.0	[(1.7715550423402533, 14.41089299461126), (3.7...	POLYGON ((68 217, 70 216, 72 216, 73 215, 75 2...	20.291765089571808	...	red	red	0.285170	0.128388	0.087745	0.077448	0.156783	0.413558	0.010297	0.165193
1	760	1	71.391949	196.740581	115.39641876807232	23	871.5	[(14.108051252629565, 14.759418626888504), (14...	POLYGON ((86 212, 86 210, 88 209, 90 206, 91 2...	21.374369189708005	...	red	red	0.295008	0.120923	0.049924	0.079961	0.174085	0.415931	-0.030037	0.129884
2	494	2	71.042601	189.803625	120.58961482031928	23	892.0	[(11.45739910313901, 16.69637518684604), (12.4...	POLYGON ((83 207, 84 205, 86 205, 86 203, 88 2...	20.40135288822979	...	red	red	0.289602	0.138168	0.000000	0.075685	0.151434	0.427770	-0.075685	0.075685
3	391	3	74.068707	186.231001	116.3744297518984	21	857.5	[(11.43129251700681, 16.26899902818269), (12.4...	POLYGON ((86 203, 87 201, 89 201, 90 199, 91 1...	20.399578962898765	...	red	red	0.346440	0.141443	0.063597	0.081153	0.204996	0.487883	-0.017556	0.144751
4	444	4	82.523703	180.657591	114.95010692219705	27	780.5	[(11.97629724535554, 15.842408712363863), (15....	POLYGON ((95 197, 99 190, 100 188, 100 184, 10...	20.334182996872435	...	red	red	0.410676	0.142739	0.097041	0.075581	0.267937	0.553416	0.021461	0.172622
5	339	5	91.56938	176.723927	107.8440407924095	26	749.5	[(8.930620413609077, 15.776072937513874), (11....	POLYGON ((101 193, 104 191, 106 190, 107 188, ...	19.75199745076159	...	red	red	0.410029	0.143001	0.020484	0.078858	0.267028	0.553029	-0.058374	0.099342
6	1599	6	99.556633	171.751282	108.24163657932809	27	747.5	[(6.943366778149397, 15.748717948717967), (8.9...	POLYGON ((107 188, 109 187, 111 187, 112 186, ...	19.572237562684293	...	red	red	0.468155	0.153945	0.089358	0.075129	0.314211	0.622100	0.014228	0.164487
7	771	7	111.74149	168.659517	111.0764782026885	29	827.5	[(9.758509566968783, 16.840483383685807), (13....	POLYGON ((122 186, 126 182, 128 181, 130 177, ...	21.12904241487818	...	red	red	0.435630	0.157703	0.074146	0.076080	0.277927	0.593334	-0.001934	0.150227
8	2107	8	118.414195	170.740411	109.3563041130157	29	843.0	[(3.085804665875841, 17.75958877026494), (5.08...	POLYGON ((122 189, 124 188, 126 188, 129 186, ...	19.280903420341502	...	red	red	0.462927	0.143977	0.098798	0.074690	0.318950	0.606905	0.024108	0.173489
9	742	9	123.609063	172.62404	111.3521091648572	27	868.0	[(6.890937019969272, 18.875960061443948), (11....	POLYGON ((131 192, 136 186, 138 185, 138 183, ...	20.297499900252678	...	red	red	0.448082	0.134867	0.085831	0.077782	0.313215	0.582949	0.008049	0.163613
10	932	10	128.309751	174.805423	117.85407190410241	28	943.5	[(5.1902490726020005, 21.69457692987106), (8.1...	POLYGON ((134 197, 137 194, 139 194, 140 192, ...	21.883407857379485	...	red	red	0.438709	0.134207	0.090692	0.077265	0.304502	0.572915	0.013427	0.167958
11	926	11	132.018802	171.702995	119.41223997479155	22	979.5	[(8.481197890079955, 19.797005274800057), (11....	POLYGON ((141 192, 144 190, 146 189, 147 185, ...	22.238618483986546	...	red	red	0.422886	0.120466	0.082897	0.077427	0.302419	0.543352	0.005469	0.160324
12	1088	12	138.011852	169.775298	123.72726948395658	24	1019.5	[(7.488147784861837, 20.7247016511362), (10.48...	POLYGON ((146 191, 149 189, 151 188, 155 183, ...	22.60726816764416	...	red	red	0.435315	0.142490	0.084443	0.080801	0.292825	0.577805	0.003642	0.165244
13	1231	13	142.618794	160.895712	122.58311404261416	22	1034.0	[(7.881205673758842, 20.604287556415215), (8.8...	POLYGON ((151 182, 152 180, 154 180, 158 176, ...	22.183475397887342	...	red	red	0.453756	0.136354	0.086885	0.079014	0.317402	0.590111	0.007871	0.165899
14	997	14	150.315073	148.52005	116.72921462019963	21	931.0	[(5.184926602219832, 19.979949874686724), (7.1...	POLYGON ((156 169, 158 168, 159 167, 162 164, ...	20.49377315803756	...	red	red	0.514422	0.144622	0.095644	0.077009	0.369800	0.659043	0.018636	0.172653
15	126	15	154.636106	146.383226	111.20916221628806	20	853.5	[(5.8638937707479215, 19.116774067564933), (7....	POLYGON ((161 166, 163 163, 164 161, 170 156, ...	19.415746732400837	...	red	red	0.568665	0.138583	0.091990	0.079130	0.430081	0.707248	0.012860	0.171120
16	1255	16	162.668709	147.5103	117.57152710834744	23	938.5	[(8.831291067305983, 17.98969987568816), (10.8...	POLYGON ((172 166, 174 165, 175 164, 178 161, ...	21.00608140822603	...	red	red	0.539604	0.124982	0.094654	0.075592	0.414622	0.664586	0.019063	0.170246
17	1256	17	168.9485	150.571808	120.6614177273773	25	972.5	[(8.551499571551005, 18.928191945158517), (11....	POLYGON ((178 170, 181 167, 182 166, 184 166, ...	21.168613687183537	...	red	red	0.568870	0.126345	0.148925	0.076883	0.442524	0.695215	0.072043	0.225808
18	921	18	174.48235	154.967305	120.29186150469945	22	991.5	[(6.017650025214323, 18.532694570516043), (8.0...	POLYGON ((181 174, 183 173, 185 173, 188 171, ...	21.530132238319275	...	red	red	0.528195	0.143308	0.084726	0.075086	0.384887	0.671504	0.009640	0.159812
19	62	19	178.590729	155.676407	116.45701582740757	26	924.0	[(9.909271284271284, 16.82359307359306), (13.9...	POLYGON ((189 173, 193 169, 195 168, 197 164, ...	20.892016825017176	...	red	red	0.580624	0.123004	0.094927	0.079263	0.457619	0.703628	0.015665	0.174190
20	1113	20	182.900713	156.213012	118.24709943782678	29	935.0	[(9.599286987522305, 17.286987522281663), (12....	POLYGON ((193 174, 196 171, 198 171, 199 169, ...	20.43092323866347	...	red	red	0.620549	0.129632	0.125887	0.079245	0.490917	0.750180	0.046642	0.205133
21	155	21	185.487459	156.238095	119.41348240555209	28	917.0	[(9.01254089422028, 18.26190476190476), (10.01...	POLYGON ((195 175, 196 173, 198 173, 199 171, ...	20.582639699001785	...	red	red	0.652733	0.143318	0.117107	0.078463	0.509415	0.796052	0.038644	0.195570
22	153	22	192.547256	158.620088	118.48769254872398	29	984.0	[(11.95274390243901, 17.879911924119256), (14....	POLYGON ((205 177, 208 172, 210 171, 211 159, ...	21.284755391810073	...	red	red	0.608483	0.156621	0.081050	0.079037	0.451862	0.765104	0.002013	0.160086
23	1195	23	197.982806	154.678331	118.8756897169512	26	964.5	[(11.517193710039749, 17.821669258683244), (12...	POLYGON ((210 173, 211 171, 213 171, 214 169, ...	21.43305300355499	...	red	red	0.680469	0.143481	0.129001	0.075977	0.536989	0.823950	0.053025	0.204978
24	1634	24	204.461785	155.853535	120.16909925048742	27	990.0	[(8.038215488215485, 20.646464646464636), (14....	POLYGON ((213 177, 219 172, 221 171, 221 165, ...	22.072990112755598	...	red	red	0.651663	0.135318	0.122854	0.078299	0.516345	0.786981	0.044555	0.201152
25	1636	25	206.212968	152.10557	118.6064053696176	26	957.5	[(4.2870322019147125, 19.39442993907744), (6.2...	POLYGON ((211 172, 213 171, 215 171, 218 169, ...	20.542740181176683	...	red	red	0.697712	0.140687	0.125190	0.075497	0.557026	0.838399	0.049693	0.200687
26	1807	26	207.437396	137.793207	117.92703272504544	24	1001.0	[(11.062604062604066, 17.706793206793208), (17...	POLYGON ((219 156, 225 151, 226 149, 226 141, ...	21.24463148132436	...	red	red	0.712731	0.131604	0.170525	0.076659	0.581127	0.844334	0.093865	0.247184
27	1942	27	211.625281	128.103946	122.55025591783964	21	1039.0	[(10.874719281360285, 17.396053897978817), (13...	POLYGON ((223 146, 226 143, 228 143, 229 141, ...	21.601933255197757	...	red	red	0.678145	0.127676	0.152555	0.076267	0.550469	0.805820	0.076288	0.228821
28	2048	28	217.412929	115.897897	120.13888808576206	20	1014.5	[(8.087070806637115, 16.602102842122548), (10....	POLYGON ((226 133, 228 132, 229 131, 231 131, ...	20.86133357675962	...	red	red	0.707885	0.141205	0.185136	0.075670	0.566680	0.849090	0.109466	0.260806
29	1341	29	213.428847	101.455485	116.33514833812384	18	951.0	[(7.071153172099542, 15.044514546091833), (9.0...	POLYGON ((221 117, 223 116, 225 116, 227 116, ...	20.98690323787094	...	red	red	0.749624	0.148988	0.203990	0.078850	0.600636	0.898612	0.125140	0.282840
30	2328	30	211.173929	88.751024	112.82286368397108	16	895.0	[(1.326070763500951, 15.748975791433892), (3.3...	POLYGON ((213 105, 215 104, 216 103, 226 101, ...	20.013190419211078	...	red	red	0.837930	0.174839	0.281621	0.086489	0.663092	1.012769	0.195132	0.368111
31	26	31	211.111431	82.658611	113.29503427027856	16	869.0	[(8.388569236670492, 14.84138856923667), (11.3...	POLYGON ((220 98, 223 96, 225 95, 227 91, 229 ...	19.285968730936283	...	red	red	0.818347	0.162746	0.273464	0.093108	0.655601	0.981093	0.180356	0.366572
32	564	32	213.140527	80.534086	106.52388923243727	16	797.0	[(2.3594730238393993, 14.965913843580097), (4....	POLYGON ((216 96, 218 95, 219 93, 226 90, 228 ...	18.85278914637469	...	red	red	0.973233	0.156409	0.418751	0.093105	0.816825	1.129642	0.325646	0.511856
33	460	33	216.308993	77.98453	108.33332741146353	16	808.0	[(1.1910066006600744, 14.515470297029708), (10...	POLYGON ((218 93, 227 89, 229 88, 234 82, 235 ...	19.064033544644598	...	red	red	0.950550	0.159047	0.388872	0.089148	0.791503	1.109597	0.299724	0.478020
34	1774	34	217.770898	79.522592	107.52326888036792	18	811.5	[(-0.27089751489012315, 15.977408092010677), (...	POLYGON ((218 96, 228 90, 230 89, 235 83, 236 ...	18.804825492688472	...	red	red	0.885376	0.162624	0.355225	0.090839	0.722751	1.048000	0.264386	0.446064
39	2156	35	218.378501	83.182325	106.83468312837819	19	791.5	[(2.1214992630027325, 15.031375026321328), (5....	POLYGON ((221 98, 224 96, 226 96, 229 93, 231 ...	18.844243298328518	...	yellow	red	0.968401	0.173102	0.428093	0.085032	0.795299	1.141504	0.343061	0.513124
40	1899	36	218.680683	86.017933	107.01288875487856	22	761.0	[(4.819316688567682, 14.89575120455541), (6.81...	POLYGON ((224 101, 226 100, 226 98, 228 98, 22...	17.53115188500524	...	yellow	red	1.000000	0.184038	0.494434	0.090789	0.815962	1.184038	0.403645	0.585223
41	2228	37	218.197835	91.137032	103.30508929922131	23	770.0	[(6.302164502164487, 14.725108225108215), (9.3...	POLYGON ((225 106, 228 104, 230 103, 233 98, 2...	16.71794828268125	...	yellow	red	0.999728	0.184762	0.528833	0.096152	0.814966	1.184490	0.432681	0.624984
42	2405	38	218.186362	91.795643	105.91250223741798	23	787.0	[(5.313638288860659, 15.015883100381188), (7.3...	POLYGON ((224 107, 226 106, 228 106, 229 104, ...	16.94191734680013	...	yellow	red	0.915916	0.164160	0.500845	0.086608	0.751756	1.080076	0.414237	0.587453
43	2615	39	217.521277	91.30479	103.41687417265716	21	775.5	[(3.9787234042553052, 14.385772619815185), (5....	POLYGON ((222 106, 224 105, 226 105, 229 103, ...	17.52449159199243	...	yellow	red	0.909171	0.161841	0.540220	0.090758	0.747330	1.071013	0.449463	0.630978
44	3084	40	219.023748	91.158047	107.67892090902448	20	779.0	[(-0.5237483953787034, 13.555626872058184), (4...	POLYGON ((219 105, 224 103, 226 103, 230 101, ...	19.07557387593079	...	yellow	red	0.937284	0.174932	0.642302	0.094959	0.762352	1.112216	0.547343	0.737261
45	3463	41	224.028936	89.69076	107.94767771994808	21	803.5	[(-5.528935905413817, 14.017216345156598), (-3...	POLYGON ((219 104, 221 103, 223 103, 225 103, ...	20.52708946899041	...	yellow	red	0.897866	0.149499	0.690332	0.092654	0.748368	1.047365	0.597679	0.782986
46	3261	42	233.199168	86.063961	115.62083409522423	19	841.0	[(-2.6991676575505323, 14.684304399524379), (-...	POLYGON ((231 101, 233 100, 235 100, 243 95, 2...	22.542124824356815	...	yellow	red	0.797878	0.137336	0.653282	0.090829	0.660542	0.935215	0.562453	0.744111
47	3287	43	237.634815	83.899027	114.86839366538844	18	787.5	[(-6.134814814814803, 14.812275132275133), (-4...	POLYGON ((232 99, 234 98, 235 97, 237 97, 239 ...	22.698134341929453	...	yellow	red	0.838053	0.147450	0.764694	0.097315	0.690603	0.985502	0.667379	0.862008
48	2475	44	242.556855	83.655277	111.96090316542035	17	727.0	[(-6.0568546538285375, 15.336084364970205), (-...	POLYGON ((237 99, 240 97, 242 96, 244 96, 248 ...	22.13965946812896	...	yellow	red	0.847670	0.149881	0.849601	0.100268	0.697789	0.997551	0.749332	0.949869
49	2544	45	245.485528	81.128107	108.83049521739171	18	702.5	[(-3.985527876631096, 14.653855278766315), (6....	POLYGON ((242 96, 252 90, 254 89, 254 87, 257 ...	22.828693886050488	...	yellow	red	0.792854	0.159972	0.832449	0.100094	0.632882	0.952826	0.732355	0.932542
50	3057	46	246.560833	80.876782	111.52935425969349	19	668.5	[(-7.06083271004735, 15.060334081276494), (-5....	POLYGON ((240 96, 242 95, 243 93, 245 93, 246 ...	22.099318550429302	...	yellow	red	0.834427	0.168367	1.000000	0.109938	0.666060	1.002795	0.890062	1.109938
51	2686	47	247.410141	78.870321	106.58318341313534	17	664.0	[(-2.910140562249012, 11.962349397590359), (2....	POLYGON ((245 91, 250 88, 252 87, 256 86, 258 ...	22.288453200065845	...	yellow	red	0.723494	0.160034	0.920759	0.112462	0.563461	0.883528	0.808297	1.033220
52	903	48	251.905195	84.599728	110.58229965913571	13	770.0	[(3.59480519480519, 12.78311688311689), (10.59...	POLYGON ((256 98, 263 94, 265 93, 265 91, 267 ...	21.42531062433394	...	yellow	green	0.588110	0.145967	0.836388	0.103356	0.442143	0.734077	0.733032	0.939743
53	985	49	248.816795	90.524167	120.3272226708876	14	977.5	[(6.683205456095493, 14.631884057971021), (7.6...	POLYGON ((256 106, 257 104, 262 101, 264 100, ...	23.10645662458693	...	yellow	green	0.440164	0.146223	0.687557	0.099044	0.293941	0.586386	0.588512	0.786601
54	1058	50	243.853229	92.434794	126.19690621118964	13	1089.0	[(1.646770737679816, 17.5754514845424), (3.646...	POLYGON ((246 111, 248 110, 250 110, 255 107, ...	22.53293727713466	...	yellow	green	0.351567	0.134351	0.656282	0.100711	0.217216	0.485918	0.555571	0.756994
55	1021	51	242.183908	93.715079	129.91287125032758	14	1160.0	[(3.316091954022994, 17.436350574712648), (5.3...	POLYGON ((246 112, 248 111, 250 111, 253 109, ...	22.734219225270902	...	yellow	green	0.303865	0.124952	0.685436	0.098547	0.178914	0.428817	0.586888	0.783983
56	1097	52	240.704864	97.399249	128.80137306505006	15	1165.0	[(4.7951359084406135, 17.685693848354788), (6....	POLYGON ((246 116, 248 115, 249 114, 252 111, ...	22.357377886606056	...	yellow	green	0.251089	0.121489	0.658426	0.096912	0.129600	0.372578	0.561513	0.755338
57	1202	53	240.922222	95.655919	130.5049334495447	15	1200.0	[(1.5777777777777544, 18.41083333333333), (10....	POLYGON ((243 115, 252 111, 254 110, 260 100, ...	23.395698169359886	...	yellow	green	0.200703	0.114593	0.659935	0.096220	0.086110	0.315297	0.563715	0.756155
58	1280	54	243.494198	90.377168	130.1159309136902	15	1206.5	[(1.0058019063406505, 17.851636966431826), (4....	POLYGON ((245 109, 248 107, 250 106, 252 106, ...	23.76582596982824	...	yellow	green	0.153571	0.103614	0.655110	0.098401	0.049957	0.257186	0.556709	0.753511
59	1289	55	246.158782	85.040545	131.6973474161899	14	1226.0	[(-0.6587819467101781, 18.4184339314845), (10....	POLYGON ((246 104, 257 100, 259 99, 261 96, 26...	22.985828831614352	...	yellow	green	0.126221	0.096435	0.740154	0.093846	0.029786	0.222656	0.646308	0.834000
35	1236	56	248.417777	82.971134	131.88291495639214	14	1238.5	[(6.082223119364812, 17.52886556318127), (9.08...	POLYGON ((255 101, 258 99, 260 98, 261 96, 263...	23.25770672129052	...	green	green	0.083804	0.087922	0.759840	0.091644	-0.004118	0.171727	0.668197	0.851484
36	1135	57	247.543466	81.087209	129.60892096092562	15	1204.0	[(5.956533776301228, 17.412790697674424), (15....	POLYGON ((254 99, 264 93, 266 92, 269 87, 270 ...	22.796772308990608	...	green	green	0.052204	0.088779	0.794799	0.094798	-0.036575	0.140983	0.700001	0.889597
37	1193	58	248.17074	81.75852	131.00663191374827	15	1227.5	[(6.329260013577738, 17.741479972844544), (11....	POLYGON ((255 100, 260 97, 262 96, 264 96, 266...	22.999463921251163	...	green	green	0.017624	0.086703	0.797485	0.103413	-0.069080	0.104327	0.694072	0.900898
38	1313	59	249.813302	83.264847	127.59110780359201	15	1181.5	[(10.68669770066299, 17.235153054027364), (13....	POLYGON ((261 101, 264 99, 266 98, 270 93, 271...	23.063837581979733	...	green	green	0.000000	0.084420	0.878646	0.103917	-0.084420	0.084420	0.774729	0.982564

60 rows × 21 columns

In [11]:

df['sign'] = np.sign(df.mean_red - df.mean_green)
df['sign_diff'] = df.sign.diff()
(df.hvplot.line(x='frame', y='sign', responsive=True) * df.hvplot.line(x='frame', y='sign_diff', color='red', responsive=True) + trackmate_utils.draw_fucci_measurement_merged_track(merged_track, red_segmentation_map, green_segmentation_map, red_stack, green_stack)).cols(1)

df['sign'] = np.sign(df.mean_red - df.mean_green) df['sign_diff'] = df.sign.diff() (df.hvplot.line(x='frame', y='sign', responsive=True) * df.hvplot.line(x='frame', y='sign_diff', color='red', responsive=True) + trackmate_utils.draw_fucci_measurement_merged_track(merged_track, red_segmentation_map, green_segmentation_map, red_stack, green_stack)).cols(1)

Out[11]:

In [12]:

def calculate_frame_offset(merged_track, green_segmentation_map, green_stack, red_segmentation_map, red_stack):
    df = trackmate_utils.measure_merged(merged_track, green_segmentation_map, green_stack, red_segmentation_map, red_stack)
    df['sign'] = np.sign(df.mean_red - df.mean_green)
    df['sign_diff'] = df.sign.diff()
    result = df.query('sign_diff == -2')
    # print(len(result))
    return None if result.empty or len(result) != 1 else result.frame.item()

def calculate_frame_offset(merged_track, green_segmentation_map, green_stack, red_segmentation_map, red_stack): df = trackmate_utils.measure_merged(merged_track, green_segmentation_map, green_stack, red_segmentation_map, red_stack) df['sign'] = np.sign(df.mean_red - df.mean_green) df['sign_diff'] = df.sign.diff() result = df.query('sign_diff == -2') # print(len(result)) return None if result.empty or len(result) != 1 else result.frame.item()

In [13]:

frame_offsets = [calculate_frame_offset(metric.merge_tracks(row.red_track,row.green_track), green_segmentation_map, green_stack, red_segmentation_map, red_stack) for row in valid_tracks.itertuples(index=False)]
valid_tracks['frame_offset'] = frame_offsets
valid_tracks

frame_offsets = [calculate_frame_offset(metric.merge_tracks(row.red_track,row.green_track), green_segmentation_map, green_stack, red_segmentation_map, red_stack) for row in valid_tracks.itertuples(index=False)] valid_tracks['frame_offset'] = frame_offsets valid_tracks

Out[13]:

	red_track	green_track	metric	frame_offset
0	32	40	1.018302	44.0
2	10	53	1.123107	51.0
3	31	1	1.134302	22.0
4	29	11	1.153568	6.0
6	40	47	1.197313	47.0
7	25	58	1.197919	55.0
8	0	41	1.218965	47.0
9	63	22	1.254325	40.0
10	59	56	1.431540	NaN
11	68	37	1.435427	46.0
12	65	45	1.470829	48.0
13	54	35	1.493277	43.0
14	51	48	1.505361	50.0
16	2	34	1.526296	46.0
17	4	0	1.550255	23.0
18	34	54	1.581644	NaN
19	50	20	1.650130	41.0
20	46	2	1.682199	23.0
21	61	42	1.744963	43.0
22	28	39	1.752087	44.0
24	33	23	1.757821	37.0
26	35	4	1.841479	19.0
27	70	8	1.901044	26.0
28	38	55	1.947493	NaN
29	30	21	2.004808	NaN
30	3	52	2.027253	NaN

In [34]:

tracks_with_valid_offsets = valid_tracks.dropna()
tracks_with_valid_offsets.describe()

tracks_with_valid_offsets = valid_tracks.dropna() tracks_with_valid_offsets.describe()

Out[34]:

	red_track	green_track	metric	frame_offset
count	21.000000	21.000000	21.000000	21.000000
mean	37.952381	29.047619	1.457570	38.142857
std	21.900859	18.610417	0.268677	12.966440
min	0.000000	0.000000	1.018302	6.000000
25%	28.000000	11.000000	1.197919	26.000000
50%	35.000000	35.000000	1.493277	43.000000
75%	54.000000	42.000000	1.682199	47.000000
max	70.000000	58.000000	1.901044	55.000000

In [17]:

l = []
for row in tracks_with_valid_offsets.itertuples(index=False):
    merged_track = metric.merge_tracks(row.red_track,row.green_track)
    measured_track = trackmate_utils.measure_merged(merged_track, green_segmentation_map, green_stack, red_segmentation_map, red_stack)
    measured_track['aspect'] = pd.to_numeric(measured_track.ELLIPSE_MAJOR)/pd.to_numeric(measured_track.ELLIPSE_MINOR)
    measured_track['frame'] = measured_track.frame - row.frame_offset
    measured_track['id'] = f'{row.red_track}_{row.green_track}'

    l.append(measured_track)

df2 = pd.concat(l)

l = [] for row in tracks_with_valid_offsets.itertuples(index=False): merged_track = metric.merge_tracks(row.red_track,row.green_track) measured_track = trackmate_utils.measure_merged(merged_track, green_segmentation_map, green_stack, red_segmentation_map, red_stack) measured_track['aspect'] = pd.to_numeric(measured_track.ELLIPSE_MAJOR)/pd.to_numeric(measured_track.ELLIPSE_MINOR) measured_track['frame'] = measured_track.frame - row.frame_offset measured_track['id'] = f'{row.red_track}_{row.green_track}' l.append(measured_track) df2 = pd.concat(l)

In [18]:

df2.hvplot(kind='line', x='frame', y='aspect', by='id')

df2.hvplot(kind='line', x='frame', y='aspect', by='id')

Out[18]:

In [32]:

df3 = pd.DataFrame()
df3['aspect'] = df2.groupby('frame').aspect.mean()
df3['std'] = df2.groupby('frame').aspect.std()
df3['aspect_top'] = df3.aspect + df3['std']
df3['aspect_bottom'] = df3.aspect - df3['std']
#
df3.aspect.hvplot() * df3.hvplot.area(
            x="frame", y="aspect_bottom", y2="aspect_top", responsive=True, min_height=200
        ).opts(alpha=0.3)
# df3.columns

df3 = pd.DataFrame() df3['aspect'] = df2.groupby('frame').aspect.mean() df3['std'] = df2.groupby('frame').aspect.std() df3['aspect_top'] = df3.aspect + df3['std'] df3['aspect_bottom'] = df3.aspect - df3['std'] # df3.aspect.hvplot() * df3.hvplot.area( x="frame", y="aspect_bottom", y2="aspect_top", responsive=True, min_height=200 ).opts(alpha=0.3) # df3.columns

Out[32]:

In [35]:

df3 = pd.DataFrame()
df3['aspect'] = df2.groupby('frame').AREA.mean()
df3['std'] = df2.groupby('frame').AREA.std()
df3['aspect_top'] = df3.aspect + df3['std']
df3['aspect_bottom'] = df3.aspect - df3['std']
#
df3.aspect.hvplot() * df3.hvplot.area(
            x="frame", y="aspect_bottom", y2="aspect_top", responsive=True, min_height=200
        ).opts(alpha=0.3)
# df3.columns

df3 = pd.DataFrame() df3['aspect'] = df2.groupby('frame').AREA.mean() df3['std'] = df2.groupby('frame').AREA.std() df3['aspect_top'] = df3.aspect + df3['std'] df3['aspect_bottom'] = df3.aspect - df3['std'] # df3.aspect.hvplot() * df3.hvplot.area( x="frame", y="aspect_bottom", y2="aspect_top", responsive=True, min_height=200 ).opts(alpha=0.3) # df3.columns

Out[35]:

In [36]:

df3 = pd.DataFrame()
df3['ar_2'] = df2.groupby('frame').PERIMETER / np.sqrt(df2.groupby('frame').AREA)
df3['aspect'] = df3.groupby('frame').ar_2.mean()
df3['std'] = df3.groupby('frame').ar_2.std()
df3['aspect_top'] = df3.aspect + df3['std']
df3['aspect_bottom'] = df3.aspect - df3['std']
#
df3.aspect.hvplot() * df3.hvplot.area(
            x="frame", y="aspect_bottom", y2="aspect_top", responsive=True, min_height=200
        ).opts(alpha=0.3)

df3 = pd.DataFrame() df3['ar_2'] = df2.groupby('frame').PERIMETER / np.sqrt(df2.groupby('frame').AREA) df3['aspect'] = df3.groupby('frame').ar_2.mean() df3['std'] = df3.groupby('frame').ar_2.std() df3['aspect_top'] = df3.aspect + df3['std'] df3['aspect_bottom'] = df3.aspect - df3['std'] # df3.aspect.hvplot() * df3.hvplot.area( x="frame", y="aspect_bottom", y2="aspect_top", responsive=True, min_height=200 ).opts(alpha=0.3)

C:\Users\leo\AppData\Local\Temp\ipykernel_20300\2399088044.py:2: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.
  df3['ar_2'] = df2.groupby('frame').PERIMETER / np.sqrt(df2.groupby('frame').AREA)

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
AttributeError: 'float' object has no attribute 'sqrt'

The above exception was the direct cause of the following exception:

TypeError                                 Traceback (most recent call last)
Input In [36], in <cell line: 2>()
      1 df3 = pd.DataFrame()
----> 2 df3['ar_2'] = df2.groupby('frame').PERIMETER / np.sqrt(df2.groupby('frame').AREA)
      3 df3['aspect'] = df3.groupby('frame').ar_2.mean()
      4 df3['std'] = df3.groupby('frame').ar_2.std()

TypeError: loop of ufunc does not support argument 0 of type float which has no callable sqrt method

3. Identify Matching Tracks¶

As S phase progresses, contrast on red channel decreases while increasing in the green channel. These contrast dynamics bleed into the segmentation and vary the size of a segment. As such, the S phase, during which segmentation on both channels is possible, provides an option to both merge tracks from each channel and getting a better estimate of the size of the nucleus.

For a given pair of tracks $R$, $G$ that overlap for $t_{overlap}$ we can define a Cartesian similarity metric of the form: $$S=\frac{\sum_{t_{overlap,min}}^{t_{overlap,max}}\sqrt{[R_{X}(t)-G_{X}(t)]^{2}+[R_{Y}(t)-G_{Y}(t)]^{2}}}{t_{overlap,max}-t_{overlap,min}}$$ Where $$min(t_{R})<=t_{overlap}<=max(t_{G})$$ Which estimates the average deviation between the two tracks in units of $\frac{pixel}{frame}$

In [8]:

green_segmentation_map = utils.read_stack(base_data_path / 'green_segmented.tiff')
tm_green = trackmate_utils.TrackmateXML(base_data_path / 'green_segmented.tiff.xml')

red_track = tm_red.trace_track(0)
green_track = tm_green.trace_track(0)

green_segmentation_map = utils.read_stack(base_data_path / 'green_segmented.tiff') tm_green = trackmate_utils.TrackmateXML(base_data_path / 'green_segmented.tiff.xml') red_track = tm_red.trace_track(0) green_track = tm_green.trace_track(0)

Let's look at candidate tracks red-0 and green-0:

In [9]:

red_track.head()

red_track.head()

Out[9]:

	ID	frame	POSITION_X	POSITION_Y	PERIMETER	image_id	AREA	ROI	roi_polygon	mean_red	std_red	mean_green	std_green	low_red	high_red	low_green	high_green
0	856	0	247.581341	293.123523	95.61413819380628	41	606.5	[(5.918658972245112, 18.376477054135762), (8.9...	POLYGON ((254 312, 257 307, 258 305, 259 299, ...	0.010738	0.104057	0.077642	0.076447	-0.093318	0.114795	0.001195	0.154089
1	894	1	262.158762	285.241765	105.93964862074475	38	759.0	[(6.34123847167325, 18.258234519104064), (8.34...	POLYGON ((269 304, 271 303, 271 301, 274 298, ...	0.000000	0.112771	0.043456	0.080206	-0.112771	0.112771	-0.036750	0.123662
2	518	2	275.38465	265.978358	104.46013970824129	34	747.0	[(7.1153502900490935, 14.521642124051766), (9....	POLYGON ((283 281, 285 280, 286 278, 288 278, ...	0.001430	0.118055	0.000000	0.077172	-0.116626	0.119485	-0.077172	0.077172
3	401	3	283.703855	262.742857	104.04837559547113	31	735.0	[(7.796145124716531, 13.757142857142867), (12....	POLYGON ((292 277, 297 274, 299 273, 300 271, ...	0.059190	0.143261	0.052387	0.079176	-0.084072	0.202451	-0.026789	0.131563
4	517	4	288.930523	260.915313	100.04485365944433	40	646.5	[(8.569476669244636, 11.584686774941986), (13....	POLYGON ((298 273, 303 270, 305 269, 306 267, ...	0.145866	0.128231	0.098255	0.074736	0.017635	0.274098	0.023519	0.172990

In [10]:

green_track.head()

green_track.head()

Out[10]:

	ID	frame	POSITION_X	POSITION_Y	PERIMETER	image_id	AREA	ROI	roi_polygon
0	247	5	263.440317	291.522857	88.41281378798725	10	525.0	[(11.05968253968257, 11.977142857142837), (12....	POLYGON ((275 304, 276 302, 278 301, 278 299, ...
1	166	6	272.387504	287.83557	87.00580543253196	10	521.5	[(9.112496005113428, 11.664429530201346), (11....	POLYGON ((282 300, 284 299, 286 296, 287 294, ...
2	17	7	280.07243	287.447819	94.78718006414792	10	642.0	[(6.427570093457916, 14.05218068535828), (10.4...	POLYGON ((287 302, 291 298, 293 297, 294 295, ...
3	288	8	286.350168	286.534632	99.54663927460682	10	693.0	[(7.14983164983164, 12.965367965367989), (9.14...	POLYGON ((294 300, 296 299, 297 297, 299 297, ...
4	389	9	288.332898	284.215622	105.08835412502395	10	766.0	[(5.16710182767622, 13.284377719756321), (7.16...	POLYGON ((294 298, 296 297, 298 297, 300 297, ...

The frame column indicates the tracks are overlapping temporally. Let's see if they overlap spatially:

In [11]:

trackmate_utils.view_red_green_track([red_stack, green_stack], red_track, green_track, frame=8)

trackmate_utils.view_red_green_track([red_stack, green_stack], red_track, green_track, frame=8)

Out[11]:

As seen above, the tracks intersect, but do not follow a similar path. It's also clear that at frame 8, the cell location does not overlap. As indicated above, we can calculate a similarity metric for these two tracks:

In [12]:

metric = trackmate_utils.CartesianSimilarity(tm_red, tm_green)
metric.calculate_metric(red_track_id=0, green_track_id=0)

metric = trackmate_utils.CartesianSimilarity(tm_red, tm_green) metric.calculate_metric(red_track_id=0, green_track_id=0)

Out[12]:

53.954147393090814

Similarly, we can calculate a metric for all possible track pairs:

In [13]:

metric_df = metric.calculate_metric_for_all_tracks()
metric_df.sort_values('metric', ascending=True).head()

metric_df = metric.calculate_metric_for_all_tracks() metric_df.sort_values('metric', ascending=True).head()

100%|██████████| 5184/5184 [00:14<00:00, 346.86it/s]

Out[13]:

	red_track	green_track	metric
2344	32	40	1.018302
1377	19	9	1.101308
773	10	53	1.123107
2233	31	1	1.134302
2099	29	11	1.153568

Based on the table above, red track 32 and green track 40 should match up pretty well:

In [14]:

red_track = tm_red.trace_track(32)
green_track = tm_green.trace_track(40)
trackmate_utils.view_red_green_track([red_stack, green_stack], red_track, green_track)

red_track = tm_red.trace_track(32) green_track = tm_green.trace_track(40) trackmate_utils.view_red_green_track([red_stack, green_stack], red_track, green_track)

Out[14]:

In [15]:

metric_df.query('metric < 10').metric.hvplot.hist()

metric_df.query('metric < 10').metric.hvplot.hist()

Out[15]:

In [16]:

metric_df.query('2 < metric < 10')

metric_df.query('2 < metric < 10')

Out[16]:

	red_track	green_track	metric
268	3	52	2.027253
1146	15	66	2.984784
1643	22	59	2.470495
2181	30	21	2.004808
3115	43	19	6.059927
4023	55	63	3.131836

In [70]:

# red_track = tm_red.trace_track(43)
# green_track = tm_green.trace_track(19)
red_track = tm_red.trace_track(30)
green_track = tm_green.trace_track(21)
trackmate_utils.view_red_green_track([red_stack, green_stack], red_track, green_track, frame=42)

# red_track = tm_red.trace_track(43) # green_track = tm_green.trace_track(19) red_track = tm_red.trace_track(30) green_track = tm_green.trace_track(21) trackmate_utils.view_red_green_track([red_stack, green_stack], red_track, green_track, frame=42)

Out[70]:

4. Measure Merged Tracks¶

Colorful plot showing red/yellow/green tracks and a flouresence time plot\

In [41]:

df = metric.merge_tracks(red_track_id=30, green_track_id=21)

df = metric.merge_tracks(red_track_id=30, green_track_id=21)

In [42]:

df.sort_values('frame')

df.sort_values('frame')

Out[42]:

	ID	frame	POSITION_X	POSITION_Y	PERIMETER	image_id	AREA	ROI	roi_polygon	color	source_track
0	718	0	145.030227	163.693012	125.33054812633623	22	901.5	[(11.4697726012202, 11.806988352745435), (13.4...	POLYGON ((157 176, 159 175, 163 175, 164 174, ...	red	red
1	741	1	149.173954	168.741993	128.99426723294698	20	983.5	[(20.326046432808, 12.758007117437728), (21.32...	POLYGON ((170 182, 171 180, 171 178, 173 177, ...	red	red
2	492	2	152.348485	171.77013	130.94655166861943	21	962.5	[(17.151515151515156, 13.729870129870136), (18...	POLYGON ((170 186, 171 184, 173 184, 174 182, ...	red	red
3	390	3	156.796843	176.663781	129.06424194635238	20	982.0	[(15.703156822810598, 14.836218601493528), (22...	POLYGON ((173 192, 180 188, 181 186, 183 183, ...	red	red
4	443	4	169.444444	177.348399	131.4679621358243	26	1062.0	[(16.055555555555543, 16.151600753295668), (19...	POLYGON ((186 194, 189 192, 191 191, 194 186, ...	red	red
5	338	5	181.742109	173.718119	131.36082021898807	25	1056.0	[(15.757891414141426, 17.781881313131294), (17...	POLYGON ((198 192, 200 191, 202 188, 204 187, ...	red	red
6	1585	6	194.315309	170.128553	130.98605948579228	26	1049.5	[(8.184691122756874, 20.37144672066063), (10.1...	POLYGON ((203 191, 205 190, 207 190, 209 190, ...	red	red
7	763	7	206.218106	167.849004	123.60216180843078	28	978.5	[(14.281894055527175, 18.650996423096586), (18...	POLYGON ((221 187, 225 183, 226 181, 226 175, ...	red	red
8	2101	8	214.156015	164.848577	120.86521463430552	27	907.5	[(7.343985307621665, 19.651423324150585), (10....	POLYGON ((222 185, 225 183, 227 182, 229 182, ...	red	red
9	731	9	220.131111	167.885185	121.22565986229465	25	900.0	[(10.368888888888875, 18.61481481481482), (13....	POLYGON ((231 187, 234 185, 236 184, 239 179, ...	red	red
10	944	10	225.79107	172.066755	123.95114441827712	29	942.5	[(11.708930150309442, 19.43324491600356), (15....	POLYGON ((238 192, 242 188, 244 187, 245 183, ...	red	red
11	960	11	232.071949	171.887614	123.61291164546542	25	915.0	[(7.428051001821473, 20.612386156648455), (9.4...	POLYGON ((240 193, 242 192, 244 192, 245 191, ...	red	red
12	1101	12	233.151844	168.834816	118.24712223146368	25	899.5	[(8.34815638317582, 19.665184361682435), (13.3...	POLYGON ((242 189, 247 186, 249 185, 250 181, ...	red	red
13	1247	13	235.302352	160.544058	126.27382070233604	23	949.5	[(10.197647884851676, 19.955941723714233), (12...	POLYGON ((246 181, 248 180, 249 179, 252 176, ...	red	red
14	1032	14	238.531952	152.851473	128.5628046122555	23	1001.5	[(11.968047928107836, 18.648527209186227), (13...	POLYGON ((251 172, 253 171, 255 171, 259 167, ...	red	red
15	127	15	240.522328	148.489549	132.82193283195625	21	1052.5	[(13.977672209026139, 19.0104513064133), (14.9...	POLYGON ((255 168, 256 166, 258 166, 260 165, ...	red	red
16	1237	16	241.973095	141.511344	141.2619136665493	21	1146.0	[(13.526905177428716, 19.988656195462482), (15...	POLYGON ((256 162, 258 161, 260 161, 264 157, ...	red	red
17	1226	17	248.769481	136.605597	136.82378353388197	22	1078.0	[(16.73051948051949, 18.894403215831773), (18....	POLYGON ((266 156, 268 155, 269 154, 272 149, ...	red	red
18	891	18	249.824427	131.430821	134.0791209031914	19	1048.0	[(14.675572519083971, 19.06917938931298), (17....	POLYGON ((265 151, 268 149, 270 148, 272 144, ...	red	red
19	54	19	250.445381	127.749376	135.48573019755784	22	1068.0	[(17.054619225967514, 17.75062421972534), (19....	POLYGON ((268 146, 270 145, 272 142, 274 141, ...	red	red
20	1051	20	254.497906	125.766338	136.086419052908	23	1114.5	[(14.002093614475825, 19.733662329893818), (16...	POLYGON ((269 146, 271 145, 272 144, 275 141, ...	red	red
21	142	21	256.189006	126.409906	137.79744455399282	22	1134.0	[(17.310993533215765, 19.090094062316282), (19...	POLYGON ((274 146, 276 145, 276 143, 278 142, ...	red	red
22	141	22	258.955238	126.993333	141.5390818709381	23	1225.0	[(15.544761904761913, 19.50666666666666), (18....	POLYGON ((275 147, 278 145, 280 144, 282 140, ...	red	red
23	1144	23	261.845357	128.93807	136.8748279180853	21	1150.5	[(15.654642908880191, 17.561929595827905), (17...	POLYGON ((278 147, 280 146, 281 145, 284 142, ...	red	red
24	1608	24	259.566951	126.989837	136.812267298496	21	1172.5	[(14.933049040511719, 17.51016346837241), (19....	POLYGON ((275 145, 280 142, 282 141, 283 139, ...	red	red
27	1615	25	266.878741	125.806623	135.1169069292797	21	1141.5	[(16.621258577894594, 16.404730617608408), (18...	POLYGON ((284 142, 286 141, 287 140, 290 137, ...	yellow	red
28	1799	26	271.636779	115.25946	140.48433766379102	20	1132.0	[(19.863221436984702, 16.462897526501763), (21...	POLYGON ((292 132, 294 131, 296 131, 296 129, ...	yellow	red
29	1932	27	284.954156	110.713004	142.9881729591448	19	1127.0	[(19.545844424726454, 17.251848565513157), (20...	POLYGON ((305 128, 306 126, 308 126, 312 119, ...	yellow	red
30	2042	28	292.859839	103.279019	144.94307400523576	18	1201.0	[(15.640160976963614, 18.862614487926734), (20...	POLYGON ((309 122, 314 119, 316 118, 316 116, ...	yellow	red
31	1315	29	294.923801	87.094489	140.6249006881293	16	1133.0	[(18.57619888202413, 18.987202118270076), (20....	POLYGON ((314 106, 316 105, 316 103, 317 101, ...	yellow	red
32	2325	30	293.779073	74.822738	139.99034726589903	13	1136.5	[(17.720926822114677, 18.10881360903359), (19....	POLYGON ((312 93, 314 92, 315 91, 316 89, 318 ...	yellow	red
33	18	31	299.536421	67.359804	139.11984777958693	12	1112.0	[(14.963579136690669, 17.547362110311752), (15...	POLYGON ((315 85, 316 83, 318 83, 319 81, 321 ...	yellow	red
34	554	32	301.627546	59.920107	134.74052824587886	10	1088.5	[(13.872454448017152, 16.780278670953912), (15...	POLYGON ((316 77, 318 76, 320 76, 321 74, 322 ...	yellow	red
35	454	33	304.127693	53.814788	133.6679912674727	10	1013.5	[(15.37230718631804, 16.051307350764674), (16....	POLYGON ((320 70, 321 68, 323 68, 324 66, 326 ...	yellow	red
36	444	34	309.374932	53.813522	127.3604291992227	5	919.5	[(15.125067971723752, 15.4205183976799), (18.1...	POLYGON ((325 70, 328 67, 330 67, 331 65, 333 ...	yellow	green
37	637	35	308.934026	53.79858	129.91010582746156	5	890.5	[(16.565974171813593, 14.505334081976414), (17...	POLYGON ((326 69, 327 67, 329 67, 331 66, 332 ...	yellow	green
38	591	36	310.106737	51.838931	132.04286187524482	6	851.0	[(18.393262828045465, 13.527614571092833), (20...	POLYGON ((329 66, 331 65, 331 63, 333 62, 334 ...	yellow	green
39	671	37	307.409933	50.207912	122.2625311414868	7	792.0	[(17.090067340067378, 11.292087542087543), (22...	POLYGON ((325 62, 330 59, 331 57, 331 51, 331 ...	yellow	green
40	720	38	307.700038	51.625051	128.3373467592068	7	876.5	[(15.799961969956314, 12.932876972808515), (20...	POLYGON ((324 65, 329 62, 331 61, 332 57, 333 ...	yellow	green
41	534	39	305.75884	52.343755	127.5163814176686	6	839.0	[(17.741160111243573, 11.981922924116013), (19...	POLYGON ((324 65, 326 64, 326 62, 328 61, 329 ...	yellow	green
42	706	40	307.257904	51.633318	130.85965406226356	7	922.5	[(19.242095754290858, 10.84878048780488), (22....	POLYGON ((327 63, 330 61, 332 60, 334 54, 334 ...	yellow	green
43	499	41	312.977087	49.130937	121.44125444160726	6	796.5	[(16.52291274325171, 11.262816488805193), (20....	POLYGON ((330 61, 334 57, 336 56, 336 52, 337 ...	yellow	green
25	753	42	301.775593	42.119199	99.02562265223223	6	470.5	[(-2.27559334041797, 18.38080056677294), (2.72...	POLYGON ((300 61, 305 52, 306 51, 306 49, 306 ...	green	green
26	562	43	300.408819	35.671898	59.64942284741085	6	223.0	[(2.091180866965601, 9.828101644245145), (3.09...	POLYGON ((303 46, 304 44, 306 43, 306 41, 306 ...	green	green

In [45]:

red_track.hvplot.line(x='frame', y='AREA').opts(color='red') * green_track.hvplot.line(x='frame', y='AREA').opts(color='green')

red_track.hvplot.line(x='frame', y='AREA').opts(color='red') * green_track.hvplot.line(x='frame', y='AREA').opts(color='green')

Out[45]:

In [47]:

df.sort_values('frame').hvplot.line(x='frame', y='AREA')

df.sort_values('frame').hvplot.line(x='frame', y='AREA')

Out[47]:

In [69]:

trackmate_utils.draw_fucci_measurement_merged_track(df.sort_values('frame'), red_segmentation_map=red_segmentation_map, green_segmentation_map=green_segmentation_map, red_stack=red_stack, green_stack=green_stack)

trackmate_utils.draw_fucci_measurement_merged_track(df.sort_values('frame'), red_segmentation_map=red_segmentation_map, green_segmentation_map=green_segmentation_map, red_stack=red_stack, green_stack=green_stack)

Out[69]:

In [61]:

metric_df.query('red_track == 0').sort_values('metric')

metric_df.query('red_track == 0').sort_values('metric')

Out[61]:

	red_track	green_track	metric
41	0	41	1.218965
0	0	0	53.954147
51	0	51	59.848973
54	0	54	69.392551
23	0	23	71.639376
...	...	...	...
18	0	18	inf
26	0	26	inf
70	0	70	inf
12	0	12	inf
71	0	71	inf

72 rows × 3 columns

In [68]:

red_track = tm_red.trace_track(0)
green_track = tm_green.trace_track(41)
(trackmate_utils.draw_fucci_measurement(red_track, segmentation_map=red_segmentation_map, red_stack=red_stack, green_stack=green_stack) + trackmate_utils.draw_fucci_measurement(green_track, segmentation_map=green_segmentation_map, red_stack=red_stack, green_stack=green_stack)).cols(1)

red_track = tm_red.trace_track(0) green_track = tm_green.trace_track(41) (trackmate_utils.draw_fucci_measurement(red_track, segmentation_map=red_segmentation_map, red_stack=red_stack, green_stack=green_stack) + trackmate_utils.draw_fucci_measurement(green_track, segmentation_map=green_segmentation_map, red_stack=red_stack, green_stack=green_stack)).cols(1)

Out[68]:

In [66]:

merged_track = metric.merge_tracks(red_track_id=0, green_track_id=41).sort_values('frame')
trackmate_utils.draw_fucci_measurement_merged_track(merged_track, red_segmentation_map=red_segmentation_map,green_segmentation_map=green_segmentation_map, red_stack=red_stack, green_stack=green_stack)

merged_track = metric.merge_tracks(red_track_id=0, green_track_id=41).sort_values('frame') trackmate_utils.draw_fucci_measurement_merged_track(merged_track, red_segmentation_map=red_segmentation_map,green_segmentation_map=green_segmentation_map, red_stack=red_stack, green_stack=green_stack)

Out[66]:

In [67]:

green_track

green_track

Out[67]:

	ID	frame	POSITION_X	POSITION_Y	PERIMETER	image_id	AREA	ROI	roi_polygon	mean_red	std_red	mean_green	std_green	low_red	high_red	low_green	high_green
0	649	35	316.717593	136.551768	79.64602509175263	17	396.0	[(5.782407407407391, 13.948232323232332), (8.7...	POLYGON ((323 151, 326 148, 326 146, 326 138, ...	0.984145	0.099880	0.000000	0.077061	0.884264	1.084025	-0.077061	0.077061
1	611	36	308.494175	131.378475	96.16906101941909	17	629.5	[(7.00582472862061, 17.121525019857017), (7.00...	POLYGON ((316 149, 316 147, 318 146, 319 144, ...	0.947828	0.162661	0.050474	0.081992	0.785167	1.110489	-0.031518	0.132466
2	682	37	305.209424	126.599767	93.03889558186627	18	573.0	[(4.2905759162303525, 16.900232693426403), (6....	POLYGON ((310 144, 312 143, 313 141, 315 141, ...	1.000000	0.124225	0.127877	0.076111	0.875775	1.124225	0.051766	0.203988
3	743	38	303.868108	124.014528	104.16852474999983	18	728.5	[(5.631892015557071, 19.48547243193778), (6.63...	POLYGON ((310 144, 311 142, 313 141, 313 137, ...	0.860234	0.166754	0.098167	0.082747	0.693480	1.026988	0.015420	0.180914
4	546	39	302.888387	121.191983	110.21802579685925	18	829.5	[(5.611613421740003, 19.30801687763713), (11.6...	POLYGON ((309 141, 315 131, 316 129, 317 113, ...	0.803333	0.183644	0.099482	0.088451	0.619689	0.986978	0.011031	0.187933
5	730	40	305.293521	121.343872	111.78886654398724	19	854.0	[(7.206479313036709, 19.156128024980475), (9.2...	POLYGON ((313 141, 315 140, 315 138, 316 136, ...	0.829141	0.175254	0.219876	0.088124	0.653887	1.004395	0.131753	0.308000
6	512	41	310.334758	119.324311	114.83058307593892	19	877.5	[(6.165242165242148, 21.175688509021853), (7.1...	POLYGON ((317 141, 318 139, 320 138, 320 136, ...	0.785522	0.164038	0.256289	0.093470	0.621484	0.949560	0.162819	0.349759
7	784	42	316.46057	111.020709	121.53816309898573	17	1006.0	[(8.039430086149764, 22.479290921139835), (11....	POLYGON ((325 134, 328 129, 329 127, 329 123, ...	0.683811	0.185125	0.214465	0.096208	0.498686	0.868935	0.118258	0.310673
8	581	43	319.328647	105.826591	120.91893629983507	18	1013.5	[(9.171353395823076, 21.673408978786384), (12....	POLYGON ((329 128, 332 125, 333 124, 333 114, ...	0.688070	0.180238	0.312774	0.100902	0.507832	0.868307	0.211872	0.413676
9	893	44	318.343868	102.169112	113.47044022127878	17	886.0	[(7.15613243039877, 20.3308878856283), (10.156...	POLYGON ((326 123, 329 121, 331 120, 331 118, ...	0.752405	0.183564	0.450146	0.100994	0.568840	0.935969	0.349152	0.551140
10	819	45	321.270005	95.925367	118.88603011049838	13	943.5	[(7.2299947005829495, 21.574633456986405), (10...	POLYGON ((329 118, 332 113, 333 111, 333 109, ...	0.635602	0.168242	0.368562	0.100882	0.467360	0.803843	0.267680	0.469443
11	851	46	317.308411	96.886812	118.45237633064113	14	963.0	[(5.191588785046747, 20.613187954309453), (12....	POLYGON ((323 118, 330 114, 331 112, 331 98, 3...	0.640369	0.185819	0.509983	0.115486	0.454550	0.826188	0.394497	0.625469
12	955	47	317.889931	108.548371	123.42534410025003	16	1013.0	[(12.610069101678164, 19.95162882527147), (13....	POLYGON ((331 129, 332 127, 334 127, 335 125, ...	0.539567	0.195965	0.452740	0.122367	0.343602	0.735532	0.330372	0.575107
13	912	48	326.427583	117.284287	125.88430863308278	17	1084.0	[(13.072416974169755, 19.21571340713406), (16....	POLYGON ((340 137, 343 135, 345 134, 346 132, ...	0.495641	0.181212	0.519599	0.119652	0.314430	0.676853	0.399947	0.639251
14	990	49	330.797491	126.255947	125.24046302168784	19	1023.0	[(13.702508960573482, 19.244053437601835), (17...	POLYGON ((345 146, 349 142, 351 141, 351 135, ...	0.471791	0.180427	0.585780	0.123954	0.291364	0.652218	0.461825	0.709734
15	1064	50	327.622528	136.044461	125.4265307879459	19	1036.5	[(13.877472262421634, 19.455539475799952), (15...	POLYGON ((342 156, 344 155, 347 150, 348 148, ...	0.421247	0.171965	0.628832	0.123622	0.249282	0.593212	0.505209	0.752454
16	1028	51	328.277471	142.018314	129.50062541763197	21	1087.5	[(11.222528735632181, 21.481685823754788), (14...	POLYGON ((340 164, 343 162, 345 161, 346 159, ...	0.374320	0.168580	0.694100	0.120334	0.205740	0.542900	0.573767	0.814434
17	1103	52	328.740119	147.224087	129.6986529196534	21	1117.5	[(9.759880686055226, 22.275913497390007), (12....	POLYGON ((339 170, 342 167, 344 167, 345 165, ...	0.309009	0.157665	0.686471	0.123432	0.151344	0.466674	0.563039	0.809902
18	1247	53	328.544781	148.780991	128.93006675505313	22	1124.0	[(8.955219454329779, 22.719009489916942), (11....	POLYGON ((338 172, 341 170, 343 169, 344 167, ...	0.257684	0.131923	0.695434	0.120218	0.125761	0.389606	0.575216	0.815652
19	1329	54	329.162236	152.193248	132.29021509448825	23	1091.0	[(8.337763519706698, 24.306752215093184), (9.3...	POLYGON ((338 177, 339 175, 341 174, 341 172, ...	0.214178	0.127807	0.743948	0.117663	0.086371	0.341986	0.626285	0.861610
20	1346	55	330.191879	154.64417	132.57310695979845	24	1196.5	[(6.308120908204501, 25.85582950271626), (11.3...	POLYGON ((337 181, 342 175, 343 173, 343 167, ...	0.163897	0.118372	0.811582	0.121828	0.045524	0.282269	0.689755	0.933410
21	1295	56	330.390826	152.86468	138.89179099420363	23	1233.5	[(4.1091744358870415, 25.635319551411953), (7....	POLYGON ((335 179, 338 177, 340 177, 344 170, ...	0.113736	0.108379	0.807228	0.125445	0.005357	0.222115	0.681783	0.932672
22	1144	57	331.084755	153.957338	140.78973357123965	24	1318.5	[(3.41524459613197, 26.542662116040958), (8.41...	POLYGON ((335 181, 340 178, 342 177, 343 175, ...	0.062697	0.102544	0.774885	0.124644	-0.039846	0.165241	0.650241	0.899530
23	1234	58	330.702821	152.36401	138.84001574920967	23	1217.0	[(4.7971788551082, 25.13599013968775), (7.7971...	POLYGON ((336 178, 339 176, 341 175, 344 170, ...	0.027535	0.087361	0.877299	0.127565	-0.059826	0.114896	0.749734	1.004864
24	1360	59	329.141154	155.600516	137.9833994372124	23	1195.5	[(5.358845671267261, 25.899484176774024), (6.3...	POLYGON ((335 182, 336 180, 338 180, 339 178, ...	0.000000	0.085407	1.000000	0.130722	-0.085407	0.085407	0.869278	1.130722

In [85]:

tv = trackmate_utils.TrackViewer(red_stack,green_stack, tm_red, tm_green, metric)

tv = trackmate_utils.TrackViewer(red_stack,green_stack, tm_red, tm_green, metric)

Calculating similarity metric: 100%|██████████| 5184/5184 [00:15<00:00, 344.21it/s]

In [86]:

tv.view()

tv.view()

Out[86]:

In [82]:

tv.view_type_wdgt

tv.view_type_wdgt

Out[82]:

In [ ]: